Leidos

As such, candidates should have successful, proven, and demonstrable experience leading proposals and winning competitive research and development efforts, and then leading high-performing teams in the development and integration of software-based solutions for customers such as DARPA and other branches of the Department of Defense.. The Principal ML Research Scientist will also have a hands-on roll and is expected to customize and create various machine learning algorithms to operate over multi-domain data and optimizing the performance of those algorithms on the data.. M.S degree in Electrical Engineering, Computational Linguistics, Computer Science, Mathematics, or related technical field.. At least 10 years of industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in the area of natural language processing, human language understanding, computational linguistics.. Ph. D. in Electrical Engineering, Computational Linguistics, Computer Science, Mathematics, or related technical field.

research scientist

Description
The Leidos Innovations Center is looking for a Principal Research Scientist in the area of Machine Learning (ML) who has a proven track record in developing technology-based approaches that yield novel, innovative capabilities while advancing the state of the art.
Primary Responsibilities
The principal research scientist will serve in the role of principal investigator on contract R&D and internal R&D programs, engaging R&D customers and transition partners to develop new business opportunities and leading teams of researchers and engineers in the development, adaptation, and extension of innovative ML-based approaches and solutions across a range of technical areas and application domains, for diverse and often disparate types of data and complexity, and for projects that are inherently both fundamental and applied in nature.
The innovative technical solutions will advance the state of the art in machine learning and/or artificial intelligence while addressing long-term problems of importance to national security. As such, candidates should have successful, proven, and demonstrable experience leading proposals and winning competitive research and development efforts, and then leading high-performing teams in the development and integration of software-based solutions for customers such as DARPA and other branches of the Department of Defense.
The Principal ML Research Scientist will also have a hands-on roll and is expected to customize and create various machine learning algorithms to operate over multi-domain data and optimizing the performance of those algorithms on the data. They will develop automation to extract and prepare features from multi-domain datasets. They will adapt NLP libraries/toolkits that include transformer models like BERT and ChatGPT, as well as Stanford CoreNLP, Spacy, NLTK, Word2Vec, and Gensim.
Basic Qualifications
M.S degree in Electrical Engineering, Computational Linguistics, Computer Science, Mathematics, or related technical field.(Ph.D. is preferred)
At least 10 years of industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in the area of natural language processing, human language understanding, computational linguistics.
At least 5 years of hands-on experience adapting the following technologies in the development of novel technology-based approaches as part of research projects: NumPy, SciPy, scikit-learn, TensorFlow, Pytorch, Keras, Genism, etc.
Strong and proven customer relationship skills including the ability to discover the true technical challenges and requirements associated with opportunities, recommending alternative technical approaches, and shaping future opportunities.
Understanding of transformers and foundation models
Python proficiency
Self-starter with high intellectual curiosity
Great communication skills, able to explain language model results to a non-technical audience
Proficient in data exploration techniques and tools
Must be a U.S Citizen
Ability to obtain a DoD Secret clearance with potential eligibility for Top Secret.
Preferred Qualifications
Ph.D. in Electrical Engineering, Computational Linguistics, Computer Science, Mathematics, or related technical field.
Track record of extending ML and AI tools and algorithms for new challenges
Experience applying and leading the application of ML/AI-based approaches and techniques in fundamental research contexts, to problems in complex domains, under conditions of uncertainty, and dynamic and evolving technical challenges
Proven track record in proposing, winning, and executing work with customers such as DARPA
Ability to work in a fast-paced environment
Excellent written and oral skills in communicating technical information with an ability to present complex technical information clearly and coherently
Proven experience forming strong teams composed of members from academia and industry for competitive research and development opportunities.
Practical understanding of generative models
Experience programming machine learning algorithms for GPUs
Understanding of Convolutional Neural Nets
Experience adapting large language models technologies
Discernment of when and how to use machine learning regulation
Experience adapting ML algorithms and tools with operational workflows for customers in the US government
LInC
Original Posting Date: 2024-02-23 While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range: Pay Range $122,200.00 - $220,900.00 The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.<br/><br/>#J-18808-Ljbffr

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